Pharmaceutical Payments to Japanese Board-Certified Infectious Disease Specialists: A Four-Year Retrospective Analysis of Payments from 92 Pharmaceutical Companies between 2016 and 2019
Bibliographic record
Abstract
Backgrounds: Conflict of interest with pharmaceutical companies is one of the most concerned issues in infectious diseases. However, there is a lack of whole picture of detailed payments in Japan. Methods: This retrospective study assessed financial relationships between pharmaceutical companies and all infectious disease specialists board-certified by the Japanese Association for Infectious Disease, using publicly disclosed payment data from 92 major pharmaceutical companies. Descriptive analyses were conducted for the payments. Payment trends were examined by the generalized estimating equations. Results: Of 1614 board-certified infection disease specialists, 1055 (65.4%) received a total of $17,784,070 payments, corresponding to 21,680 contracts between 2016 and 2019. The mean ± SD and median (interquartile range: IQR) were $16,857 ± $45,010 and $3183 ($938–$11,250) in payments. All board executive members of Japanese Association of Infectious Disease received higher payments averaging $163,792. There were no significant changes in payments per specialist (annual change rate: −1.4% [95% CI: −4.7–2.3%], p = 0.48) and prevalence of specialists with payments (annual change rate: −1.4% [95% CI: −3.1–0.2%], p = 0.093) over the four years. Conclusion: There were substantial financial relationships between pharmaceutical companies and board-certified infectious disease specialists in Japan. Furthermore, high ranked specialists such as those in the executive board had stronger financial ties with the companies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".